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Enteric infectious diseases claim more than 1 million lives annually and are among the top ten causes of death in children younger than 5 years. Remarkable global investment has been dedicated to enteric infectious disease prevention and control; however, the shifting global health landscape is testing the continuance of progress. To evaluate the current status and guide future interventions, we present the latest epidemiological estimates of enteric infectious diseases from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023 and assess progress towards the Global Action Plan for the Prevention and Control of Pneumonia and Diarrhoea (GAPPD) mortality target of fewer than 20 deaths per 100 000 children younger than 5 years by 2025. We quantified the incidence, mortality, and disability-adjusted life-years (DALYs) of enteric infectious diseases by age, sex, and year across 204 countries and territories from 1990 to 2023. In GBD 2023, the following were considered under the category of enteric infectious diseases: diarrhoeal diseases, enteric fever (typhoid and paratyphoid), invasive non-typhoidal Salmonella spp (iNTS) infections, and other intestinal infectious diseases. We also examined 15 aetiologies contributing to diarrhoeal diseases. Incidence and prevalence were estimated with DisMod-MR (version 2.1), a Bayesian meta-regression tool, drawing on data from systematic reviews, population-based surveys, claims data, and hospital sources. Cause-specific mortality was modelled with Cause of Death Ensemble Modelling based on data from sources including vital registration, mortality surveillance, verbal autopsy, and minimally invasive tissue sampling. Years of life lost and years lived with disability were computed and combined to derive DALYs. For aetiology-specific estimation, population-attributable fractions (PAFs) for 15 pathogens were derived with a counterfactual framework. Point estimates and 95% uncertainty intervals (UIs) were generated from 250 draws from the posterior distribution. In 2023, enteric infectious diseases resulted in an estimated 1·27 million (95% UI 0·963-1·68) deaths globally, declining from 3·69 million (3·04-4·56) in 1990. The global age-standardised mortality rate (ASMR) decreased from 74·1 (62·0-92·9) per 100 000 population to 16·4 (12·6-21·3) per 100 000 population during the same period. Diarrhoeal diseases accounted for most deaths in 2023 (1·11 million [0·811-1·54]), followed by enteric fever and iNTS. South Asia and sub-Saharan Africa remained the most affected regions in 2023, with 599 000 (441 000-882 000) and 501 000 (373 000-648 000) deaths due to enteric infectious diseases, respectively, predominantly from diarrhoeal disease. Rotavirus was the leading cause of all-age diarrhoeal disease deaths (PAF 16·3% [12·0-21·5]), followed by norovirus (10·2% [2·4-17·0]) and Shigella spp (9·3% [5·4-15·2]). Among children younger than 5 years, PAFs of deaths due to diarrhoeal diseases were 40·2% (32·5-48·5) for rotavirus, 24·0% (15·1-36·7) for Shigella spp, and 23·4% (13·7-34·3) for adenovirus. Across 204 countries and territories, 141 met the GAPPD mortality target in 2023. The driving aetiologies among countries that did not meet the target in 2023 varied slightly by GBD super-region, but the highest or second-highest number of deaths in children younger than 5 years were consistently attributed to rotavirus. Astrovirus and sapovirus, newly included in GBD 2023, were responsible for 24 600 (6290-49 000) and 18 800 (4650-44 400) deaths, respectively, in 2023, mainly in children younger than 5 years. Our findings show that mortality and ASMRs of enteric infectious diseases declined substantially between 1990 and 2023. This decline is consistent with the expansion of public health measures and broader socioeconomic development. However, the burden in 2023 remains considerably high, with the highest mortality concentrated in sub-Saharan Africa and south Asia. Considering that more than a quarter of all countries had yet to meet the GAPPD mortality target in 2023, sustained efforts are needed to address the persistent burden in affected countries and to adapt to the changing global health landscape. Gates Foundation.

This retrospective, cross-sectional study analyzed clinical CT scans from 367 Indian subjects (199 healthy; 168 with TMJ ankylosis) from a tertiary hospital to compare mandibular morphometric parameters between Indian subjects with healthy and ankylosed temporomandibular joints (TMJs) of differing age groups and sex. Furthermore, the study compared mandibular morphometry of the Indian population with that of other countries. Key mandibular parameters, including ramus length and condyle width, were measured from 3D reconstructions. Two-sample z-tests and paired t-tests were used (p&#x202f;<&#x202f;0.05). Ramus length was significantly shorter in ankylosis subjects across all age groups and sexes, as compared with healthy subjects, while condyle width was higher. However, both ramus length and condyle width in ankylosis group increased with age. The minimum observed ramus lengths in the ankylosis group were 14.01&#x202f;mm, 20.37&#x202f;mm, and 24.93&#x202f;mm in the pre-pubertal, pubertal, and adult age cohorts, respectively, while the maximum observed condyle widths were 25.42&#x202f;mm, 32.05&#x202f;mm, and 36.32&#x202f;mm for the same age cohorts. In unilateral cases, the affected side had shorter ramus length and wider condyle than the unaffected side. When comparing the mandibles of the healthy adult Indian group with those from other countries, Indian mandibles were found to be longer than Brazilian and Chinese, but shorter than Australian and Korean counterparts. This study aimed to establish to what extent TMJ ankylosis influences mandibular structure. The study identified two key mandibular morphometries in the ankylosis group, especially ramus length and condyle width, as being significantly different from those in the healthy group in India. The study also highlighted salient country-specific differences in mandibular morphometry. These findings would be crucial in the development of population-specific TMJ implants to improve clinical outcomes.

Small renal masses (SRMs), defined as renal tumors&#x2009;<&#x2009;4&#xa0;cm, are increasingly detected due to the widespread use of imaging modalities. Data from India regarding the clinical characteristics and outcomes of SRMs remain limited. This multi-institutional study led by the Society of Genitourinary Oncologists aims to delineate the demographic, radiological, and pathological profiles of SRMs in the Indian population and evaluate management outcomes following partial nephrectomy. A retrospective analysis was conducted across multiple tertiary care centers in India from January 2013 to December 2022. Patients aged&#x2009;&#x2265;&#x2009;18&#xa0;years with SRMs undergoing partial nephrectomy were included. Data on demographics, clinical presentation, radiology (including RENAL nephrometry score), intraoperative factors, postoperative outcomes, and histopathology were analyzed. Statistical associations between renal scores, BMI, tumor stage, and histologic type were assessed. A total of 432 patients were analyzed, with a male predominance (76.6%) and mean age of 51.8&#x2009;&#xb1;&#x2009;12.9&#xa0;years. Most SRMs (80.3%) were incidentally detected. Robotic-assisted partial nephrectomy was performed in 85% of cases, with a mean operative time of 228.7&#x2009;&#xb1;&#x2009;91.8&#xa0;min and clamp time of 25.5&#x2009;&#xb1;&#x2009;9.1&#xa0;min. The overall complication rate was 7%. Clear cell RCC was the most common histology (71.1%), while benign lesions accounted for 11.6%. Positive margins were seen in 1.4% of cases. BMI correlated significantly with renal complexity (p&#x2009;=&#x2009;0.010). At a median follow-up of 36&#xa0;months, recurrence occurred in 0.9% of patients. Female patients under 45&#xa0;years had a higher incidence of benign pathology (34.1%, p&#x2009;<&#x2009;0.001). This first large-scale Indian collaborative study highlights unique epidemiologic and pathologic trends in SRMs, including lower benign histology rates and higher complexity in obese patients. Robotic partial nephrectomy demonstrated favorable perioperative and oncologic outcomes. The findings support individualized management strategies and emphasize the need for structured follow-up protocols in the Indian setting.

Data on Canalis Sinuosus (CS) morphology in South Asian populations remain limited, despite frequent anterior maxillary implant placements. This study aimed to evaluate the occurrence, positional characteristics, and morphometric features of the CS in Indian adults using cone-beam computed tomography (CBCT) and to assess sex-related differences. A cross-sectional analysis was conducted on 245 CBCT scans with intact maxillary incisors and canines. Multiplanar reconstructions were used to identify the CS and document its laterality, tooth relationship, and orientation. Measurements included canal diameter at the alveolar crest and distances to the alveolar crest, buccal cortical plate, and nasal floor. Inter-observer agreement was assessed using Cohen's &#x3ba;. Sex differences were analyzed using &#x3c7; 2 and independent-samples t-tests (&#x3b1; = 0.05). CS was detected in 67.3% of individuals, with bilateral presentation in 55.9% and unilateral in 11.4%. Detection rates were similar between sides (left: 62.4%, right: 60.8%). The canal was most frequently adjacent to the lateral incisor (44.7% left, 50.3% right), and approximately half of the canals showed palatal orientation. The mean canal diameter was 0.8 mm. Mean distances to the alveolar crest, buccal cortical plate, and nasal floor were 9.2 mm, 7.0 mm, and 11.5 mm, respectively. Males showed significantly larger canal diameters on the left side (p = 0.008), greater buccal cortical distances bilaterally (p < 0.001), and larger right nasal floor distances (p = 0.011). The CS is a frequently observed, typically bilateral anatomical structure in the anterior maxilla of Indian adults, mostly located palatal adjacent the lateral incisor. The morphometric and sex-specific data obtained provide valuable reference parameters for implant planning and minimizing surgical complications.

India accounts for one-third of the global incidence and mortality of oral cancer. The national oral cancer screening program uses Conventional Oral Examination by Primary Healthcare (PHC) workers. This subjective assessment leads to unnecessary referrals to higher centers for biopsy and false negatives due to inappropriate biopsy site selection. Angiogenesis is one of the steps in early carcinogenesis, as solid tumors, such as oral cancers, cannot grow beyond 2-3 mm in diameter without inducing their own blood supply. The increased vascular supply and metabolic rate in malignant cells lead to a rise in temperature, which can be detected by sensitive digital infrared (IR) cameras. An Artificial Intelligence-enabled automatic analysis of intraoral IR images of oral lesions can be used for screening, early detection of Stage I and II oral cancers, and biopsy site selection as an objective Point-of-Care (POC) adjunct. A standardized protocol for passive and active IR imaging of intraoral lesions (index test) with a smartphone-based IR camera will be prepared to train a Medical Scientist and Technician. IR images of already diagnosed normal, Inflammatory, potentially malignant disorders, and malignant oral lesions (N&#xa0;=&#xa0;100 each) will be used in Phase I to train an AI model to classify images as malignant or non-malignant. A second set of IR images of these oral lesions will be used in Phase II (N&#xa0;=&#xa0;100 each) for evaluating the performance of the AI model. The reference test for malignancy will be histopathology (Gold standard). The intra/inter observer reliability will be assessed using the kappa statistics A clinical trial and validation of the proof of concept are proposed for IR imaging of intraoral lesions as a noninvasive POC adjunct for early detection and screening of oral cancer by PHC workers, and for the selection of biopsy sites by surgeons. &#xa9; 2026 Wiley Periodicals LLC.

Forensic age estimation in individuals older than 50 years remains challenging because conventional skeletal indicators exhibit wide error margins in this age range. The manubriosternal joint (MSJ) is among the last joints in the human skeleton to undergo fusion, yet large-scale computed tomography (CT)-based data on its fusion patterns particularly from the Indian subcontinent are sparse. To determine the prevalence and age-sex distribution of complete MSJ fusion on CT in a large Indian cohort and to evaluate its diagnostic accuracy for forensic age estimation, with particular reference to the medico-legally relevant 55-65-year age window. In this retrospective cross-sectional observational study, MSJ fusion status was assessed on chest CT scans of 734 consecutive outpatients at a government hospital over a one-year period. Fusion was recorded as a binary variable (complete fusion vs. no fusion). Descriptive statistics, chi-square tests, binary logistic regression, and receiver operating characteristic (ROC) curve analysis were performed. Of 734 patients (age range 0-97 years), 194 (26.4%) showed complete MSJ fusion. The mean age of fused individuals was 57.2 years compared with 48.2 years in the unfused group (p&#xa0;<&#xa0;0.001). Fusion prevalence rose progressively from 0% in the 0-9-year age group to 41% in the 70-79-year group but did not exceed 44% in any decade. On logistic regression, each one-year increase in age significantly increased the odds of fusion (adjusted odds ratio [aOR] 1.032 per year, 95% CI 1.021-1.043), while sex was not a significant independent predictor. The optimal age cutoff by Youden's index was &#x2265;54 years, yielding a sensitivity of 64.9% and specificity of 57.0%, with an area under the ROC curve (AUC) of 0.642. Addition of sex to the model did not meaningfully improve discrimination (AUC 0.643). Complete MSJ fusion is significantly associated with advancing age but occurs in only a minority of individuals even beyond the seventh decade. Its moderate discriminative ability (AUC 0.642) indicates that MSJ fusion alone is insufficient for precise forensic age estimation. However, its high negative predictive value at younger thresholds may be useful as an adjunctive indicator within a multifactorial age-estimation protocol. Population-specific Indian reference data are presented for the first time from a CT-based sample of this size.

The development of hybrid metal nanoparticles (NPs) for use as computed tomography (CT) contrast agents is a promising area of research. Achieving optimal in vivo performance of imaging for NPs is challenging and depends on their geometry, materials properties, bioreactivity, and biocompatibility. In this study, we designed and developed a novel CT contrast agent composed of gold nanoparticles (AuNPs) coordinated on the surface of bismuth sulfide-core nanorods (Au@Bi2S3 NRs) utilizing a solvothermal synthesis approach. We conducted solid-state characterization of Au@Bi2S3 NRs, demonstrating their structural configuration, excellent stability, uniformity, and high crystallinity. We also tested their biocompatibility with mesenchymal stem cells and found that they were well tolerated at lower tested concentrations, with reduced viability observed at higher concentrations. To evaluate the imaging potential of Au@Bi2S3 NRs, we tested them in small animals using CT imaging. Our results showed contrast enhancement in soft tissues, indicating the retention of the particles at these locations with no local inflammatory responses. Taken together, our study provides a proof-of-concept for the robust synthesis and use of Au@Bi2S3 NRs as effective CT imaging contrast agents. Future work will explore the potential to functionalize Au@Bi2S3 NRs with therapeutic molecules for theranostic applications.

Pathologic diagnosis is a critical phase in deciding the optimal treatment procedure for dealing with colorectal cancer (CRC). Colonic polyps, precursors to CRC, can pathologically be classified into two major types: adenomatous (malignant potential) and hyperplastic (benign). Various imaging techniques, such as narrow band imaging (NBI) and white light imaging (WLI), are adopted in capturing polyp-specific features for accurate classification and have different advantages. However, the existing classification techniques mainly rely on a single imaging modality and show limited performance due to data scarcity. Recently, generative artificial intelligence has been gaining prominence in overcoming such issues, especially with various generation-controlling mechanisms using text prompts and images. However, such mechanisms require class labels to make the model respond efficiently to the provided control input. In the colonoscopy domain, such controlling mechanisms are rarely explored; specifically, the text prompt is a completely uninvestigated area. Moreover, the unavailability of expensive class-wise labels for diverse sets of images limits such explorations. This raises the key question of how diverse and clinically meaningful colonoscopy images can be generated in a text-controlled manner from limited annotated data. Therefore, in this work, we develop a novel model, PathoPolyp-Diff, that generates text-controlled synthetic images with diverse characteristics in terms of pathology, imaging modalities, and quality, enabling more effective augmentation of downstream diagnostic models. The proposed model follows a two-stage process: first, the model learns to distinguish polyp from non-polyp characteristics, and then it focuses on pathology-specific features. In the process, we introduce cross-class label learning to make the model learn features from other classes, reducing the burdensome task of data annotation. We validate the effectiveness of text-controlled synthesis and cross-class label learning by performing polyp classification (adenomatous/hyperplastic) with different imaging modalities (NBI/WLI) and text prompts. The experimental results show that incorporating the proposed synthetic images for data augmentation yields an improvement of up to 7.91% in balanced accuracy on a publicly available dataset, highlighting the utility of our approach for enhancing downstream classification performance. Moreover, cross-class label learning achieves a statistically significant improvement of up to 18.33% in balanced accuracy during video-level analysis. The code is available at https://github.com/Vanshali/PathoPolyp-Diff.

Artificial intelligence (AI) and machine learning (ML) are increasingly reshaping diagnostic radiology, particularly neuroimaging, by enabling a transition from traditional descriptive interpretation to predictive, quantitative, and precision-oriented analysis. The rising global burden of neurological and neuropsychiatric disorders, coupled with the exponential growth in imaging data complexity, has exposed the limitations of conventional, human-centered radiological assessment. This descriptive review synthesizes recent advances in AI- and ML-driven neuroimaging, with emphasis on their role in early disease detection, risk prediction, and clinical decision support. Key applications across major imaging modalities, including magnetic resonance imaging (MRI), computed tomography, positron emission tomography, functional MRI, and diffusion tensor imaging, are examined, encompassing brain tumor characterization, neurodegenerative disorders, stroke, epilepsy, and psychiatric and neurodevelopmental conditions. In addition to diagnostic performance, the review highlights AI-enabled workflow optimization and addresses critical challenges related to data heterogeneity, external validation, model interpretability, regulatory oversight, and ethical considerations. Although AI-driven approaches demonstrate substantial potential to enhance diagnostic accuracy, efficiency, and personalized patient care, their routine clinical integration remains limited by methodological and translational barriers. Overcoming these challenges through robust multicenter validation, development of explainable AI models, and sustained interdisciplinary collaboration will be essential to fully realize the promise of&#xa0;predictive neuroimaging and advance diagnostic radiology toward preventive and precision medicine.

Background Breast cancer is the most common malignancy among women worldwide and remains a leading cause of cancer-related mortality. In India, delayed presentation and limited access to organised screening programmes contribute to poorer outcomes. Community-based screening models, combined with advanced imaging techniques, may improve early detection. This study evaluates the effectiveness of screening mammography incorporating digital breast tomosynthesis (DBT) with synthesised two-dimensional imaging in a real-world urban population in Central India. Methods This community-based cross-sectional screening study involved retrospective analysis of prospectively collected data from 1275 women recruited through outreach programmes in Nagpur, India, between March 2019 and February 2020. All participants underwent full-field digital mammography (FFDM) with DBT. Imaging included two-dimensional craniocaudal views and three-dimensional mediolateral oblique tomosynthesis views, with reconstructed synthesised two-dimensional images for each breast. Breast density, BI-RADS (Breast Imaging Reporting and Data System) categories, and screening outcomes were recorded. Adjunct ultrasonography was performed in selected cases. Screening performance indicators, including cancer detection rate, recall rate, and positive predictive value for biopsy (PPV3), were calculated. Results A total of 1275 women were screened, with a mean age of 51 &#xb1; 8.09 years, and 95.8% were asymptomatic. Breast density was predominantly ACR Category B (57.4%), followed by Category C (30.2%). The majority of cases were categorised as BI-RADS 1 (75.5%) and BI-RADS 2 (15.6%), while 16 cases (1.3%) were classified as BI-RADS 4 lesions. A statistically significant association was observed between breast density and BI-RADS categories (p = 0.018), with higher BI-RADS categories more frequent in women with heterogeneously dense breasts. No significant association was found between age group and BI-RADS categories (p = 0.21). Histopathological correlation was available in four cases, with two confirmed malignancies. The cancer detection rate was 1.6 per 1000 women screened, the recall rate was 8.5%, and the PPV3 for biopsy was 50%. Conclusion Community-based breast cancer screening using FFDM combined with DBT and synthesised imaging is feasible and clinically effective in an Indian setting. DBT enhances the detection of small and occult lesions, particularly in women with dense breasts. Strengthening follow-up systems and expanding structured, imaging-based screening programmes would significantly improve early detection and outcomes in resource-limited settings.

This article aims to assess the diagnostic accuracy of Kupffer cell-specific contrast-enhanced ultrasound (Sonazoid) for characterization of suspicious malignant focal liver lesions and the diagnostic accuracy of Sonazoid in differentiating tumoral thrombosis of the portal vein from bland thrombosis. This was a single-center, prospective, cross-sectional study conducted in the Department of Radiology. Baseline gray-scale ultrasound, along with contrast-enhanced imaging, was performed in patients who met the inclusion criteria. CEUS images were read by two radiologists with an experience of 3 and 15 years, respectively. Interobserver agreement between two observers was calculated. CECT and CEMRI images were read by a third radiologist with an experience of around 7 years; he was also blinded to the histopathology and CEUS results. CECT/CEMRI was taken as a gold standard for HCC (based on the evidence-based practice/AASLD guidelines); for non-HCC lesions, histopathology was taken as a gold standard. Diagnostic accuracy, sensitivity, and positive predictive value (PPV) of CEUS were then calculated with respect to the gold standard. In eight cases included in our study, portal vein thrombosis was present, and so the diagnostic accuracy of CEUS with Sonazoid for differentiating tumoral and bland thrombosis was also calculated. CEUS with Sonazoid has a sensitivity of 90%, an accuracy of 87%, and a PPV of 96% for characterizing focal liver lesions. CEUS with Sonazoid (with respect to histopathology) has a sensitivity of 87.5%, specificity of 87.5%, and diagnostic accuracy of 77.8% for the characterization of lesions. In a limited number of patients included in our study, CEUS had a sensitivity, specificity, negative predictive value, and PPV of 100% for differentiating between tumoral and bland thrombus. CEUS is an excellent modality for differentiating tumoral from bland thrombus, and it can be safely used for lesion characterization in patients where CT/MRI contrast agent is contraindicated. In cases of diagnostic dilemma, CEUS can be used as an alternative modality. Since it is radiation free, it can be used in regular surveillance of high-risk patients.

The impact of pulmonary tuberculosis persists despite successful treatment and poses a significant burden on healthcare. Post-tuberculosis lung disease (PTLD) is defined as "evidence of a chronic respiratory abnormality, with or without symptoms, attributable at least in part to prior tuberculosis". The abnormalities include residual lung lesions on imaging, lung function abnormalities, and complications such as haemoptysis, relapse, bronchiectasis and destroyed lung among others. These lung disorders have been studied independently but a comprehensive approach to PTLD has not yet been studied. Our research was conducted to emphasise the burden of PTLD and correlate this with comorbidities. A hospital based cross sectional observational study was conducted in Department of Respiratory Medicine, MMIMSR using a self-designed proforma. A total of 150 patients with history of previously treated tuberculosis were enrolled for this study over 2 years based on the inclusion/exclusion criteria. Patient demographic information, symptomatology, comorbidities and smoking status were entered in the proforma. Chest Xray, CT chest, PFT and 2D echo findings were also collected. Data was analysed and statistically correlated using SPSS PC 25 version. P value&#xa0;<&#xa0;0.05 was considered significant. The mean age of the patients was 50.25&#xa0;&#xb1;&#xa0;15.89 years with more males (55&#xa0;%) than females (45&#xa0;%). Comorbidities included anaemia (43&#xa0;%), diabetes (28&#xa0;%) and COPD (24&#xa0;%) among others. Radiological sequelae were found in 147/150 patients. These included pulmonary fibrosis (79&#xa0;%%), total collapse (13.6&#xa0;%) multiple cavities (34.7&#xa0;%), pleural involvement (44.2&#xa0;%), bronchiectasis (40&#xa0;%) and destroyed lung (10.2&#xa0;%). On spirometry 48&#xa0;% showed a restrictive pattern, while a mixed obstructive and restrictive pattern was seen in 34&#xa0;% of cases. Tuberculosis associated obstructive pulmonary disease (TOPD) was observed in 49&#xa0;%, haemoptysis in 25&#xa0;% and relapse in 13.6&#xa0;% patients. Significant associations included diabetes with haemoptysis (p&#xa0;<&#xa0;0.01), hypertension with type II respiratory failure (p&#xa0;=&#xa0;0.01) and haemoptysis with bronchiectasis (p&#xa0;<&#xa0;0.01) and aspergilloma (p&#xa0;=&#xa0;0.001). our study underscores the wide range of lung disorders and dysfunction experienced by TB survivors, which are exacerbated by comorbidities. Hence, patient care and follow up must not end with successful treatment of TB. Digitalization of patient records is emphasized to enable follow up for identifying sequalae that may arise in future. Moreover, management of PTLD should be standardised and included in national guidelines by policy makers.

A specimen of the reticulated leatherjacket, Stephanolepis diaspros Fraser-Brunner, 1940, primarily distributed in the Red Sea and Mediterranean Sea, was recorded for the first time from the southeast coast of Bangladesh. This represents the first confirmed occurrence of the species in the eastern Indian Ocean. Species identification was verified through an integrative taxonomic approach combining morphological examination, radiographic imaging and mitochondrial cytochrome c oxidase subunit I (COX1) gene sequencing. Distinctive scale patterns were observed on different parts of the body; notably, the presence of cycloid scales associated with bristles was documented as a novel diagnostic feature. Both morphometric and genetic analyses demonstrated a high similarity to previously described S.&#x2009;diaspros specimens, with minimal intraspecific genetic divergence (0.16%-0.33%) relative to Mediterranean populations. This new distribution record extends the known biogeographical range of S.&#x2009;diaspros, suggesting potential ecological plasticity and long-distance dispersal in response to environmental changes.

Intrauterine growth restriction (IUGR) is defined as an estimated fetal weight below the 10th percentile for gestational age and is commonly associated with placental insufficiency and abnormal fetoplacental oxygenation. This study aimed to assess placental apparent diffusion coefficient (ADC) and perfusion values in IUGR using 3T magnetic resonance imaging (MRI). Sixty pregnant women (30 with IUGR and 30 controls; gestational age 20-38 weeks) underwent placental MRI on a 3T system. The imaging protocol included T2-weighted anatomical sequences, diffusion-weighted imaging (b-values: 0 and 700 s/mm2; NEX = 3), and three-dimensional pseudo-continuous arterial spin labeling (3D pCASL) perfusion imaging (TR/TE = 5000/50 ms, labeling duration = 1500 ms, post-labeling delay = 1525 ms, 30 label/control pairs). ADC and perfusion maps were generated, and multiple elliptical regions of interest (ROIs; 40-60 mm2) were placed throughout the placenta. Mean values were calculated for each subject. Mean placental perfusion was significantly lower in the IUGR group compared with controls (102.5 &#xb1; 18.7 vs. 120.2 &#xb1; 23.7 ml/100 g/min, p = 0.002). ADC values were also significantly reduced in IUGR placentas (1.83 &#xb1; 0.10 &#xd7; 10-3 mm2/s vs. 2.02 &#xb1; 0.10 &#xd7; 10-3 mm2/s, p = 0.001). Receiver operating characteristic (ROC) analysis demonstrated fair diagnostic performance for perfusion (AUC = 0.703) and excellent performance for ADC (AUC = 0.919). Both placental ADC and perfusion values were reduced in IUGR. However, because ADC is influenced by perfusion bias, the most clinically relevant finding is the direct quantification of reduced placental perfusion using 3D pCASL at 3T. This technique provides absolute perfusion values in physiological units and may serve as a valuable non-invasive biomarker of placental dysfunction in IUGR.

Gliomas are biologically and metabolically heterogeneous brain tumors whose clinical behavior is strongly influenced by lineage-defining genomic alterations such as isocitrate dehydrogenase (IDH1/2) mutation, 1p/19q-codeletion, ATRX loss, TERT promoter mutation, etc. Conventional magnetic resonance imaging (MRI) and tumor tissue biopsy are the clinical standards for diagnosis, tumor grading, and treatment planning. The conventional MRI/ magnetic resonance spectroscopy (MRS) identifies structural and vascular changes, and easy-to-measure high concentration metabolites. However, conventional MRS method suffers from spectral overlap and fails to provide a pure resonance, thus, it has limited application for estimation of difficult-to-identify and clinically relevant metabolic pool and flux changes in the tumors. Metabolic imaging using in vivo molecule tailored MRS provides a quantitative, highly precise non-invasive approach to measure tumor biochemistry in real time for ascertaining clinically relevant signatures for tumor diagnostication and prognostication. Recent developments in spectroscopic editing methods have provided quantitative MRS approaches to measure challenging metabolites such as glycine (Gly), glutamine (Gln), glutamate (Glu), 2-hydroxyglutarate (2HG), cystathionine and glutathione (GSH), in addition to routine MRS based measurements of metabolites, such as N-acetylaspartate (NAA), choline (Cho), creatine (Cr), lactate (Lac), etc. The pool of 2HG reflects epigenetic and redox remodeling in IDH-mutant tumors, whereas elevated glycine is associated with increased nucleotide demand and proliferative activity. Furthermore, molecule tailored MRS provide insights into cysteine-centered transsulfuration, antioxidant reprogramming and GSH-mediated radioresistance. Notably, these metabolic alterations often precede visible changes seen on anatomical MRI. Thus, metabolic profiling&#xa0;using molecule tailored MRS helps to find early tumor biomarkers for better diagnosis, along with the MRI. Future directions should include standardizing MRS protocols across imaging platforms, integrating metabolic markers with radio-genomics and machine-learning frameworks. Further, multi-center clinical trials and incorporating metabolic endpoints are necessary for adaptive therapy strategies. Together, MRI and MRS provide a comprehensive view of glioma biology that supports precision diagnosis, risk stratification, and individualized treatment planning, thereby advancing the goal of routine clinical adoption of metabolic imaging in neuro-oncology.

Clinical utility and dynamics of plasma biomarkers in early-onset dementia remain underexplored. To investigate plasma biomarker trajectories and their associations with clinical outcomes in early-onset Alzheimer disease (EOAD) and frontotemporal dementia (FTD). This multicenter, prospective cohort study analyzed participants in phase 1 of the Longitudinal Study of Early-onset Dementia and Family Members (LEAF), which was conducted from April 2021 through December 2023 in 34 centers across South Korea. Patients with &#x3b2;-amyloid-positive EOAD and FTD were included and underwent annual blood sampling and clinical assessment, within a follow-up period of approximately 2 years. Data were analyzed between June 2025 and March 2026. Levels of plasma phosphorylated tau 217 (p-tau217), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) biomarkers were analyzed using assays. (1) Associations of baseline biomarkers with clinical outcomes (assessed with the Mini-Mental State Examination [MMSE] and the Clinical Dementia Rating-Sum of Boxes [CDR-SB] for the EOAD group, or the frontotemporal lobar degeneration [FTLD]-modified CDR-SB for the FTD group), (2) biomarker trajectories, and (3) association of biomarker level changes and clinical outcomes. A total of 322 participants with p-tau217, GFAP, and NfL analyses were stratified into the EOAD or FTD group based on their diagnosis. The EOAD group (n&#x2009;=&#x2009;245) had a mean (SD) age of 61.8 (5.4) years and included 163 females (66.5%), while the FTD group (n&#x2009;=&#x2009;77) had a mean (SD) age of 65.1 (7.3) years and included 45 females (62.3%). In the EOAD group, higher log2-transformed baseline p-tau217, GFAP, and NfL were each associated with faster decline in the MMSE score (association estimate [SE], -0.390 [0.127], P&#x2009;=&#x2009;.002; -0.775 [0.164], P&#x2009;<&#x2009;.001; and -0.679 [0.182], P&#x2009;<&#x2009;.001, respectively) and the CDR-SB score (estimate [SE], 0.401 [0.099], P&#x2009;<&#x2009;.001; 0.535 [0.126], P&#x2009;<&#x2009;.001; and 0.693 [0.122], P&#x2009;<&#x2009;.001, respectively). In the FTD group, GFAP and NfL were associated with MMSE decline (estimate [SE], -2.118 [0.566], P&#x2009;<&#x2009;.001 and -2.360 [0.428], P&#x2009;<&#x2009;.001, respectively), whereas p-tau217 was not (estimate [SE], 0.071 [0.418], P&#x2009;=&#x2009;.87). No biomarker was associated with FTLD-modified CDR-SB score change. Longitudinally, all mean (SD) biomarker levels increased in the EOAD group (p-tau217: 0.253 [0.077] pg/mL, P&#x2009;=&#x2009;.001; GFAP: 0.173 [0.040] pg/mL, P&#x2009;<&#x2009;.001; NfL: 0.149 [0.045] pg/mL, P&#x2009;=&#x2009;.001), whereas in the FTD group, only NfL level showed an upward pattern (0.251 [0.127] pg/mL, P&#x2009;=&#x2009;.05). Annualized biomarker changes were associated with worsening clinical outcomes in the EOAD group, but not in the FTD group. GFAP and NfL level increases were associated with MMSE score decline (estimate [SE], -0.005 [0.002], P&#x2009;=&#x2009;.007 and -0.010 [0.003], P&#x2009;=&#x2009;.001, respectively), while p-tau217 level increases were associated with CDR-SB score worsening (estimate [SE], 0.072 [0.024], P&#x2009;=&#x2009;.003) in the EOAD group. In this cohort study of patients with EOAD and FTD, baseline p-tau217, GFAP, and NfL were consistently associated with clinical outcomes in the EOAD group, whereas GFAP and NfL were associated with cognition only in the FTD group. These findings demonstrate distinct characteristics of plasma biomarkers in EOAD and FTD, supporting their potential utility for risk stratification.

Background: Vitamin D deficiency (VDD) may be associated with chronic health issues, including markers of liver disease; however, evidence in American Indian adolescents is limited. Therefore, we aimed to evaluate the relationship between VDD in American Indian adolescents and markers of liver disease, including both serum and magnetic resonance imaging (MRI) markers. Methods: The Strong Heart Family Study (SHFS) is a multicenter, family-based, prospective cohort study among American Indians. We evaluated SHFS participants who were <20 years old at baseline (2001-2003; n = 308), defined VDD as hydroxyvitamin-D (25[OH]D) &#x2264; 20 ng/mL and calculated the Hepatic Steatosis Index (HSI). In 2006-2009, we measured follow-up serum markers (n = 269, median follow-up = 5.8 years, range = 3.0-8.5), and in 2018-2020, we collected MRI markers of hepatic steatosis and fibrosis (n = 33, median follow-up = 16.7 years, range = 15.3-18.1). Results: At baseline, a greater proportion of those with VDD had HSI > 36 (64.5% with VDD; p = 0.002). For participants who reported consuming alcohol, serum alkaline phosphate (ALP) increased at follow-up, which was higher for those with versus without VDD (beta = 12.24, 95% CI = 1.23-23.24). For participants who reported not consuming alcohol, ALP decreased but was not different between the VDD groups. The MRI-proton density fat fraction was higher in those with (median = 11.0%, IQR = 7.7-19.2%) versus without (median = 4.4, IQR = 1.8-6.3%) VDD at baseline (p < 0.001). Conclusions: VDD may be associated with markers of liver disease in American Indian adolescents. After 5.5 years, VDD was associated with increasing ALP in those who consume alcohol, while controlling for adiposity and other covariates. After 17 years of follow-up, VDD was associated with increased liver MRI-PDFF.

The aim of this study is to evaluate the utility of perfusion CT (PCT) in the diagnosis of pancreatic ductal adenocarcinoma (PDAC). In this ethically approved prospective study, PCT was performed in 71 patients with histologically proven PDAC. Perfusion parameters studied included blood flow (BF), blood volume (BV), permeability surface area product (PS), time to peak (TTP), peak enhancement intensity (PEI), and mean transit time (MTT). Forty-four controls with no pancreatic pathology were also studied. Out of 71 patients, 43 (60.56%) were males and 28 (39.44%) were females, with male:female ratio of 1.54, and the mean age of the patients was 50.62&#x2009;&#xb1;&#x2009;13.86 years. The mean size of the masses was 4.47&#x2009;&#xb1;&#x2009;2.43&#x2009;cm (range: 1.3-12&#x2009;cm). Among the perfusion parameters, BF and BV were found to be the most reliable for the diagnosis of pancreatic adenocarcinoma. They were reduced in PDAC (BF: 19.54&#x2009;&#xb1;&#x2009;19.85&#x2009;mL/100&#x2009;mL/min and BV: 5.14&#x2009;&#xb1;&#x2009;3.82&#x2009;mL/100&#x2009;mL) as compared with normal controls (BF: 96.91&#x2009;&#xb1;&#x2009;39.09&#x2009;mL/100&#x2009;mL/min and BV: 30.45&#x2009;&#xb1;&#x2009;12.90&#x2009;mL/100&#x2009;mL) and the difference was statistically significant ( p &#x2009;=&#x2009;0.0001). Based on ROC analysis, cut-off values of 55.25&#x2009;mL/100&#x2009;mL/min for BF and 14.42&#x2009;mL/100&#x2009;mL for BV yielded optimal sensitivity (97.2% for BF and 98.6% for BV) and specificity (91% for BF and 91% for BV) for the diagnosis of pancreatic adenocarcinoma. PCT parameters are useful in making an imaging diagnosis of PDAC and useful tool to detect isodense pancreatic masses. Approximated values of BF and BV perfusion parameters may serve as independent diagnostic predictors for the diagnosis of PDAC.

Histological grade holds great clinical significance in the management and prognosis of bladder cancer; therefore, timely and accurate prediction through non-invasive techniques such as MRI may improve health outcomes. Our objective was to create an MRI-based radiomics model that can predict the histological grade of cancer pre-operatively. In a prospective study, we gathered data from 45 bladder cancer patients who had an mpMRI scan from December 2018 to December 2022 prior to their operative procedure. Radiomics features were extracted from T2-weighted (T2W), diffusion-weighted imaging (DWI), and dynamic DCE-MRI-enhanced (DCE) MR images obtained from a 1.5&#xa0;T MRI scanner. A standard 5-point VI-RADS scoring system was also assessed for each scan. The variable clustering algorithm was applied to these features, and all cluster features were univariably assessed using receiver operating characteristic (ROC) curves. Multiple predictive models were created and cross-validated based on multivariable analysis to minimize overfitting and predict the grade of the tumor. Among 45 eligible patients, 28 (62.2%) patients had high-grade tumors and the rest 17 (37.8%) were low grade. In the adjusted analysis, only DCE-MRI based (Gray Level Co-occurrence Matrix (Gray Level Co-occurrence Matrix (GLCM))-inverse variance (OR&#x2009;=&#x2009;1.42, p&#x2009;=&#x2009;0.028), Major Axis Length (OR&#x2009;=&#x2009;1.04, p&#x2009;=&#x2009;0.03)), and age (OR&#x2009;=&#x2009;1.08, p&#x2009;=&#x2009;0.039) were associated with the high-grade bladder cancer. Our radiomics models comprising DCE-MRI-based parameters, a T2W parameter, and age yielded the highest performance for predicting grades of bladder cancer (AUC&#x2009;=&#x2009;0.91; 95% CI 0.82-1.00). These models demonstrated reasonably high predictive performance in bootstrap validation analysis as well. An mpMRI radiomics approach based on MRI has the potential to serve as a non-invasive imaging tool for preoperative grading of bladder cancer. The online version contains supplementary material available at 10.1007/s13193-025-02397-3.